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Generators, bounded draws, pivot, merge insertion: defects found while documenting

- LinearCongruential keeps its parameters, and so min() and max(), at
  run time, which a UniformRandomBitGenerator has constant:
  LinearCongruentialT< a , c , m > is the same generator with static
  constexpr min() and max(), MinStd and Mmix those of Park and Miller and
  of Knuth; min() is 1 when c = 0, as in std::linear_congruential_engine
- shuffle() and reservoirSampling() draw their indices without the bias
  of g() % j and within [ g.min() , g.max() ]: Lemire's method on a full
  word, rejection on narrower ranges, joined draws below s; the same
  draws in the universal hashes, Probing and connectedComponents()
- SparseMatrix::pivot() walks the lists as Algorithm 2.2.6S, the same
  results bit by bit, instead of a get() and a set() per entry
- reservoirSampleL() advances by std::ranges::advance(), which input
  iterators with a sized sentinel take
- mergeInsertionSort() keeps its chain in a treap of ranks, no
  std::find and no shift of a vector, the same comparisons
- smoothsort() states n < L_64 as a precondition, the limit of its
  forest of 64 bits; leonardo() loses a / 1
- optimalChange() and knapsack() check that their C + 1 places fit a
  vector before computing the size
- the duplicated includes of <algorithm>, and the comment of
  strongProbablePrimes() above it instead of above canonical()
- the tests random-ranges, generator-concepts, sparse-pivot,
  reservoir-l-input, ford-johnson-chain, smoothsort-orders and
  table-size; universal-chaining on 200 functions

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